Numpy 中输入幂和的对数

要获得输入幂和的对数，请在 Python Numpy 中使用 numpy.logaddexp() 方法。

计算 log(exp(x1) + exp(x2))。此函数在统计学中很有用，其中计算的事件概率非常小，可能超出正常浮点数的范围。在这种情况下，存储计算出的概率的对数。此函数允许以这种方式存储的概率相加。

NumPy 提供了全面的数学函数、随机数生成器、线性代数例程、傅里叶变换等。它支持广泛的硬件和计算平台，并且与分布式、GPU 和稀疏数组库配合得很好。

步骤

首先，导入所需的库 -

import numpy as np

登录输入 -

one = np.log(1e-50)
two = np.log(2.5e-50)

# 显示日志输入 -

print("Value 1...
", one)
print("Value 2...
", two)

要获得输入幂和的对数，请在 Python Numpy 中使用 numpy.logaddexp() 方法 -

res = np.logaddexp(one, two)
print("
Logarithm of the sum of exponentiations...
",res)

示例

import numpy as np

# Calculates log(exp(x1) + exp(x2)).
# This function is useful in statistics where the calculated probabilities
# of events may be so small as to exceed the range of normal floating point numbers.
# In such cases the logarithm of the calculated probability is stored.
# This function allows adding probabilities stored in such a fashion.

# Log input
one = np.log(1e-50)
two = np.log(2.5e-50)

# Display the log input
print("Value 1...
", one)
print("Value 2...
", two)

# To get the Logarithm of the sum of exponentiations of the inputs, use the numpy.logaddexp() method in Python Numpy
res = np.logaddexp(one, two)
print("
Logarithm of the sum of exponentiations...
",res)

输出

Value 1...
-115.12925464970229
Value 2...
-114.21296391782813

Logarithm of the sum of exponentiations...
-113.87649168120691

更新日期：07-Feb-2022

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